scholarly journals Quality Assessment of PROBA-V LAI, fAPAR and fCOVER Collection 300 m Products of Copernicus Global Land Service

2020 ◽  
Vol 12 (6) ◽  
pp. 1017 ◽  
Author(s):  
Beatriz Fuster ◽  
Jorge Sánchez-Zapero ◽  
Fernando Camacho ◽  
Vicente García-Santos ◽  
Aleixandre Verger ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Accuracy Assessment ◽  
Observation System ◽  
Good Precision ◽  
Area Index ◽  
Global Land ◽  
Moderate Resolution ◽  
Earth Observation System ◽  
Temporal Profiles ◽  
Absorbed Photosynthetically Active Radiation

The Copernicus Global Land Service (CGLS) provides global time series of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fAPAR) and fraction of vegetation cover (fCOVER) data at a resolution of 300 m and a frequency of 10 days. We performed a quality assessment and validation of Version 1 Collection 300 m products that were consistent with the guidelines of the Land Product Validation (LPV) subgroup of the Committee on Earth Observation System (CEOS) Working Group on Calibration and Validation (WGCV). The spatiotemporal patterns of Collection 300 m V1 LAI, fAPAR and fCOVER products are consistent with CGLS Collection 1 km V1, Collection 1 km V2 and Moderate Resolution Imagery Spectroradiometer Collection 6 (MODIS C6) products. The Collection 300 m V1 products have good precision and smooth temporal profiles, and the interannual variations are consistent with similar satellite products. The accuracy assessment using ground measurements mainly over crops shows an overall root mean square deviation of 1.01 (44.3%) for LAI, 0.12 (22.2%) for fAPAR and 0.21 (42.6%) for fCOVER, with positive mean biases of 0.36 (15.5%), 0.05 (10.3%) and 0.16 (32.2%), respectively. The products meet the CGLS user accuracy requirements in 69.1%, 62.5% and 29.7% of the cases for LAI, fAPAR and fCOVER, respectively. The CGLS will continue the production of Collection 300 m V1 LAI, fAPAR and fCOVER beyond the end of the PROBA-V mission by using Sentinel-3 OLCI as input data.

scholarly journals A comparison of methods for smoothing and gap filling time series of remote sensing observations – application to MODIS LAI products

2013 ◽  
Vol 10 (6) ◽  
pp. 4055-4071 ◽  
Author(s):  
S. Kandasamy ◽  
F. Baret ◽  
A. Verger ◽  
P. Neveux ◽  
M. Weiss
Keyword(s):  
Time Series ◽  
Missing Data ◽  
Time Course ◽  
Singular Spectrum Analysis ◽  
Gaussian Function ◽  
Gap Filling ◽  
Area Index ◽  
Filling Time ◽  
Moderate Resolution ◽  
Temporal Profiles

Abstract. Moderate resolution satellite sensors including MODIS (Moderate Resolution Imaging Spectroradiometer) already provide more than 10 yr of observations well suited to describe and understand the dynamics of earth's surface. However, these time series are associated with significant uncertainties and incomplete because of cloud cover. This study compares eight methods designed to improve the continuity by filling gaps and consistency by smoothing the time course. It includes methods exploiting the time series as a whole (iterative caterpillar singular spectrum analysis (ICSSA), empirical mode decomposition (EMD), low pass filtering (LPF) and Whittaker smoother (Whit)) as well as methods working on limited temporal windows of a few weeks to few months (adaptive Savitzky–Golay filter (SGF), temporal smoothing and gap filling (TSGF), and asymmetric Gaussian function (AGF)), in addition to the simple climatological LAI yearly profile (Clim). Methods were applied to the MODIS leaf area index product for the period 2000–2008 and over 25 sites showed a large range of seasonal patterns. Performances were discussed with emphasis on the balance achieved by each method between accuracy and roughness depending on the fraction of missing observations and the length of the gaps. Results demonstrate that the EMD, LPF and AGF methods were failing because of a significant fraction of gaps (more than 20%), while ICSSA, Whit and SGF were always providing estimates for dates with missing data. TSGF (Clim) was able to fill more than 50% of the gaps for sites with more than 60% (80%) fraction of gaps. However, investigation of the accuracy of the reconstructed values shows that it degrades rapidly for sites with more than 20% missing data, particularly for ICSSA, Whit and SGF. In these conditions, TSGF provides the best performances that are significantly better than the simple Clim for gaps shorter than about 100 days. The roughness of the reconstructed temporal profiles shows large differences between the various methods, with a decrease of the roughness with the fraction of missing data, except for ICSSA. TSGF provides the smoothest temporal profiles for sites with a % gap > 30%. Conversely, ICSSA, LPF, Whit, AGF and Clim provide smoother profiles than TSGF for sites with a % gap < 30%. Impact of the accuracy and smoothness of the reconstructed time series were evaluated on the timing of phenological stages. The dates of start, maximum and end of the season are estimated with an accuracy of about 10 days for the sites with a % gap < 10% and increases rapidly with the % gap. TSGF provides more accurate estimates of phenological timing up to a % gap < 60%.

scholarly journals Global White-Sky and Black-Sky FAPAR Retrieval Using the Energy Balance Residual Method: Algorithm and Validation

2019 ◽  
Vol 11 (9) ◽  
pp. 1004 ◽  
Author(s):  
Liu ◽  
Zhang ◽  
Xie ◽  
Liu ◽  
Song ◽  
...  
Keyword(s):  
Energy Balance ◽  
Area Index ◽  
Global Soil ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Comparison Of The Results ◽  
Spectral Mixture ◽  
Sky Conditions ◽  
Absorbed Photosynthetically Active Radiation

The fraction of absorbed photosynthetically active radiation by vegetation (FAPAR) is a key variable in describing the light absorption ability of the vegetation canopy. Most global FAPAR products, such as MCD15A2H and GEOV1, correspond to FAPAR under black-sky conditions at the satellite overpass time only. In this paper, we aim to produce both the global white-sky and black-sky FAPAR products based on the moderate resolution imaging spectroradiometer (MODIS) visible (VIS) albedo, leaf area index (LAI), and clumping index (CI) products. Firstly, a non-linear spectral mixture model (NSM) was designed to retrieve the soil visible (VIS) albedo. The global soil VIS albedo and its dynamics were successfully mapped at a resolution of 500 m using the MCD43A3 VIS albedo product and the MCD15A2H LAI product. Secondly, a method based on the energy balance residual (EBR) principle was presented to retrieve the white-sky and black-sky FAPAR using the MODIS broadband VIS albedo (white-sky and black-sky) product (MCD43A3), the LAI product (MCD15A2H) and CI products. Finally, the two EBR FAPAR products were compared with the MCD15A2H and Geoland2/BioPar version 1 (GEOV1) black-sky FAPAR products. A comparison of the results indicates that these FAPAR products show similar spatial and seasonal patterns. Direct validation using FAPAR observations from the Validation of Land European Remote sensing Instrument (VALERI) project demonstrates that the EBR black-sky FAPAR product was more accurate and had a lower bias (R2 = 0.917, RMSE = 0.088, and bias = −2.8 %) than MCD15A2H (R2 = 0.901, RMSE = 0.096, and bias = 7.6 % ) and GEOV1 (R2 = 0.868, RMSE = 0.105, and bias = 6.1%).

scholarly journals Monthly-averaged maps of surface BRDF parameters in ten spectral bands for land and water masses

2018 ◽  
Author(s):  
Philippe Blanc ◽  
Benoit Gschwind ◽  
Lionel Ménard ◽  
Lucien Wald
Keyword(s):  
Original Data ◽  
Observation System ◽  
Creative Commons ◽  
Spectral Bands ◽  
The Usa ◽  
Moderate Resolution ◽  
Earth Observation System ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Bidirectional Reflectance Distribution

Abstract. The construction of worldwide maps of surface bidirectional reflectance distribution function (BRDF) parameters is presented. The original data stems from the National Aeronautics and Space Administration (NASA) of the USA which is making available maps of BRDF parameters that are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The first parameter fiso describes the isotropic part of the BRDF while the two others fvol and fgeo describe the anisotropic part and are linked to the viewing and illuminating geometry. The original data has been averaged for each calendar month for the period 2004–2011 and a spatial completion of data was performed, especially in water-covered areas. The resulting complete maps are available in ten spectral bands: [459–479] nm, [545–565] nm, [620–670] nm, [400–700] nm, [841–876] nm, [1230–1250] nm, [1628–1652] nm, [2105–2155] nm, [250–5000] nm, [700–5000] nm, [250–5000] nm. The maps form a Global Earth Observation System of Systems (GEOSS) Data Collection of Open Resources for Everyone (Data-CORE) supporting the GEOSS Data Sharing Principles. They are referenced by the doi:10.23646/85d2cd5f-ccaa-482e-a4c9-b6e0c59d966c and available in NetCDF format under the Creative Commons license CC-BY.

scholarly journals Computationally Efficient Methods of Collocating Satellite, Aircraft, and Ground Observations

2009 ◽  
Vol 26 (8) ◽  
pp. 1585-1595 ◽  
Author(s):  
Frederick W. Nagle ◽  
Robert E. Holz
Keyword(s):  
Observation System ◽  
Computationally Efficient ◽  
Laptop Computer ◽  
Geometric Problem ◽  
Temporal Sampling ◽  
Wide Range ◽  
Moderate Resolution ◽  
Surface Measurements ◽  
Earth Observation System ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract The usefulness of measurements from satellite-borne instruments is enhanced if these measurements can be compared to measurements from other instruments mounted aboard the same or different satellite, with measurements from aircraft, or with ground measurements. The process of associating measurements from disparate instruments and platforms is referred to as collocation. In a few cases, two instruments mounted aboard the same spacecraft have been engineered to function in tandem, but commonly this is not the case. The collocation process may then become an awkward geometric problem of finding which of many observations within one dataset corresponds to an observation in another set, possibly from another platform. This paper presents methods that can be applied to a wide range of satellite, aircraft, and surface measurements that allow for efficient collocation with measurements having varying spatial and temporal sampling. Examples of applying the methods are presented that highlight the benefits of efficient collocation. This includes identifying the occurrence of simultaneous nadir observations (SNOs); collocation of sounder, imager, and active remotely sensed measurements on the NASA Earth Observation System (EOS); and collocation of the polar orbiting imager, sounder, and microwave measurements with geostationary observations. It is possible, using an inexpensive laptop computer, to collocate Moderate Resolution Imaging Spectroradiometer (MODIS) imager observations from the Aqua satellite with geostationary observations rapidly enough to deal with these measurements in real time, making either dataset, enhanced by the other, a potentially operational product. A “tool kit” is suggested consisting of computer procedures useful in collocation.

scholarly journals Efficient and Flexible Aggregation and Distribution of MODIS Atmospheric Products Based on Climate Analytics as a Service Framework

2021 ◽  
Vol 13 (17) ◽  
pp. 3541
Author(s):  
Jianyu Zheng ◽  
Xin Huang ◽  
Supriya Sangondimath ◽  
Jianwu Wang ◽  
Zhibo Zhang
Keyword(s):  
Vital Role ◽  
Parallel Execution ◽  
Observation System ◽  
Single Node ◽  
Spectral Bands ◽  
Service Oriented ◽  
Moderate Resolution ◽  
Level 3 ◽  
Earth Observation System ◽  
Moderate Resolution Imaging Spectroradiometer

MODIS (Moderate Resolution Imaging Spectroradiometer) is a key instrument onboard NASA’s Terra (launched in 1999) and Aqua (launched in 2002) satellite missions as part of the more extensive Earth Observation System (EOS). By measuring the reflection and emission by the Earth-Atmosphere system in 36 spectral bands from the visible to thermal infrared with near-daily global coverage and high-spatial-resolution (250 m ~ 1 km at nadir), MODIS is playing a vital role in developing validated, global, interactive Earth system models. MODIS products are processed into three levels, i.e., Level-1 (L1), Level-2 (L2) and Level-3 (L3). To shift the current static and “one-size-fits-all” data provision method of MODIS products, in this paper, we propose a service-oriented flexible and efficient MODIS aggregation framework. Using this framework, users only need to get aggregated MODIS L3 data based on their unique requirements and the aggregation can run in parallel to achieve a speedup. The experiments show that our aggregation results are almost identical to the current MODIS L3 products and our parallel execution with 8 computing nodes can work 88.63 times faster than a serial code execution on a single node.

scholarly journals Estimación de parámetros biofísicos de la vegetación en praderas y cultivos en Chile mediante fotografía digital hemisférica obtenidas por una cámara GoPro

2018 ◽  
pp. 1 ◽  
Author(s):  
D. Uribe ◽  
C. Mattar ◽  
F. Camacho
Keyword(s):  
Agricultural Land ◽  
Biophysical Parameters ◽  
Area Index ◽  
Active Radiation ◽  
Global Land ◽  
Green Vegetation ◽  
Agricultural Applications ◽  
Land Covers ◽  
Absorbed Photosynthetically Active Radiation

<p>The estimation of the biophysical parameters of vegetation such as LAI (Leaf Area Index), FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) and FCOVER (Fraction of Green Vegetation) have many climatic, hydrologic, ecosystem and silvo-agricultural applications. Despite the various satellite products that estimate these parameters continuously and globally, it’s necessary to continue generating <em>in situ</em> estimations to validate these remote data. It’s in this context where Digital Hemispheric Photography (DHP) technique stands out as being one of the most accurate an adaptable to operate continuously with diverse photographic equipment and field scenarios. The objective of this paper is to estimate effective LAI (LAI<sub>eff</sub>), true LAI (LAI<sub>true</sub>), FAPAR and FCOVER through the DHP method on several agricultural land covers in Chile, between the years 2015 and 2016 using a GoPro camera and the CAN-EYE software to process hemispheric photographs. The results obtained were initially compared with those provided by a CANON EOS 6D camera mounted together with a SIGMA 8mm F3.5-EX DG fisheye lens and subsequently with satellite products provided by the Copernicus Global Land service, derived from PROBA-V mission at 333 m<sup>2</sup> spatial resolution. The comparison between the CANON and GoPro shows similar values and R<sup>2 </sup>over 0,72 for all parameters. The comparison with PROBA-V resulted in values over 0,52 of R<sup>2</sup> for the parameters, and similar multitemporal patterns. It’s concluded that it’s possible to estimates LAI<sub>eff</sub>, FAPAR and FCOVER like other fish eyes cameras. Concerning PROBA-V, except for FAPAR, the estimates with the GoPro do not show much correlation. In both campaigns significant discrepancies were observed in the LAI<sub>true</sub>, which could be related to the calculation of CAN-EYE canopy clumping with the characteristics of the camera itself.</p>

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